Utah FORGE: Stress Logging Data
This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 - 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in situ stress (determined from the density logging) and the total maximum and minimum horizontal stresses. The horizontal stresses were determined from the DSI (Dipole Sonic Imager) and corrected to match the direct measurements.
Citation Formats
TY - DATA
AB - This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 - 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in situ stress (determined from the density logging) and the total maximum and minimum horizontal stresses. The horizontal stresses were determined from the DSI (Dipole Sonic Imager) and corrected to match the direct measurements.
AU - McLennan, John
DB - Geothermal Data Repository
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/1452760
KW - geothermal
KW - energy
KW - well 58-32
KW - stress
KW - 58-32 stress
KW - stress test
KW - 58-32 stress data
KW - 58-32 stress test
KW - Utah FORGE
KW - Utah
KW - Roosevelt Hot Springs
KW - UT
KW - Youngs Modulus
KW - Poisson Ratio
KW - dynamic
KW - pressure
KW - pore pressure
KW - sh max
KW - vertical
KW - horizontal
KW - stress log
KW - logging
KW - log
KW - data
KW - FORGE
KW - EGS
KW - rock properties
KW - rock props
KW - geomechanics
KW - well data
KW - in situ stress
KW - resource
KW - characterization
KW - Milford
KW - stress plot
LA - English
DA - 2018/03/14
PY - 2018
PB - Energy and Geoscience Institute at the University of Utah
T1 - Utah FORGE: Stress Logging Data
UR - https://doi.org/10.15121/1452760
ER -
McLennan, John. Utah FORGE: Stress Logging Data. Energy and Geoscience Institute at the University of Utah, 14 March, 2018, Geothermal Data Repository. https://doi.org/10.15121/1452760.
McLennan, J. (2018). Utah FORGE: Stress Logging Data. [Data set]. Geothermal Data Repository. Energy and Geoscience Institute at the University of Utah. https://doi.org/10.15121/1452760
McLennan, John. Utah FORGE: Stress Logging Data. Energy and Geoscience Institute at the University of Utah, March, 14, 2018. Distributed by Geothermal Data Repository. https://doi.org/10.15121/1452760
@misc{GDR_Dataset_1032,
title = {Utah FORGE: Stress Logging Data},
author = {McLennan, John},
abstractNote = {This spreadsheet consist of data and graphs from deep well 58-32 stress testing from 6900 - 7500 ft depth. Measured stress data were used to correct logging predictions of in situ stress. Stress plots shows pore pressure (measured during the injection testing), the total vertical in situ stress (determined from the density logging) and the total maximum and minimum horizontal stresses. The horizontal stresses were determined from the DSI (Dipole Sonic Imager) and corrected to match the direct measurements.},
url = {https://gdr.openei.org/submissions/1032},
year = {2018},
howpublished = {Geothermal Data Repository, Energy and Geoscience Institute at the University of Utah, https://doi.org/10.15121/1452760},
note = {Accessed: 2025-07-11},
doi = {10.15121/1452760}
}
https://dx.doi.org/10.15121/1452760
Details
Data from Mar 14, 2018
Last updated Mar 12, 2020
Submitted Mar 14, 2018
Organization
Energy and Geoscience Institute at the University of Utah
Contact
Greg Nash
801.585.9986
Authors
Keywords
geothermal, energy, well 58-32, stress, 58-32 stress, stress test, 58-32 stress data, 58-32 stress test, Utah FORGE, Utah, Roosevelt Hot Springs, UT, Youngs Modulus, Poisson Ratio, dynamic, pressure, pore pressure, sh max, vertical, horizontal, stress log, logging, log, data, FORGE, EGS, rock properties, rock props, geomechanics, well data, in situ stress, resource, characterization, Milford, stress plotDOE Project Details
Project Name Utah FORGE
Project Lead Lauren Boyd
Project Number EE0007080
